个体化穴位贴敷治疗OIC (1).docx
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1、摘要摘要目的:(1)研究观察个体化穴位贴敷治疗阿片类药物相关性便秘的临床疗效。(2)通过网络药理学和分子对接的方法探究穴位贴敷组方治疗阿片类药物相关性便秘的作用机制。方法:(1)临床部分:将符合纳入标准的70例阿片类药物相关性便秘患者随机分为治疗组和对照组,每组各35例。治疗组采用个体化穴位贴敷治疗,对照组予以乳果糖治疗。治疗1周后观察两组患者治疗前后首次排便时间、便秘症状评分(CCS评分)、粪便性状评分(BSFS评分)及不良反应情况,并在停药后继续随访观察1周,了解便秘复发情况。(2)网络药理学部分:利用TCMSP数据库、TCMID数据库及中国天然产物化学成分库查找穴位贴敷组方药物化学成分,
2、并查阅相关文献进行补充;进一步通过TCMSP数据库及STITCH数据库预测化学成分潜在靶点,并通过UniProt数据库将靶蛋白名转化成靶基因名;同时通过Genecards数据库、OMIM数据库及TTD数据库筛选得到与OIC相关的靶点。将药物成分所对应的靶点与疾病靶点进行映射获取交集靶点,并利用Cytoscape3.8.2软件构建“药物-化学成分-交集靶点-疾病”的关系网络;将交集靶点输入STRIING数据库构建与OIC相关的PPI网络。利用Cytoscape3.8.2软件对PPI网络进行可视化,并对网络进行拓扑结构分析,筛选穴位贴敷组方治疗OIC的关键作用靶点,同时反向寻找关键靶点所对应的化学
3、成分作为关键化学成分。应用薛定谔软件进行分子对接验证关键化学成分与关键靶点相结合的可靠性;将关键靶点输入DAVID数据库,进行GO功能富集分析以及KEGG生物通路富集分析,进一步探究穴位贴敷组方治疗OIC的作用机制。结果:(1)在治疗过程中有5例患者脱落,最终纳入65例,其中治疗组33例,对照组32例。较治疗前两组在BSFS评分、CCS评分及各单项症状评分上均存在统计学差异(P0.001);治疗后两组在排便难易程度、每次排便时间、排便辅助类型及每日排便不成功的次数上比较,无统计学意义差异(P0.05);两组在首次排便时间、粪便性状、排便频率、排便不尽感、腹部疼痛等方面比较,治疗组优于对照组(P
4、0.05);两组疗效上比较,治疗组总有效率为87.88%,优于对照组(71.88%,P0.05);在治疗过程中治疗组有1例患者出现轻度皮肤过敏,对照组2例患者出现轻度恶心,给予对症处理后症状缓解。两组复发情况上比较,治疗组复发率为20.69%明显低于对照组复发率(47.83%,P0.05),且治疗组停药复发时间也晚于对照组(P0.05)。(2)通过对穴位贴敷组方作用于OIC靶点的生物网络分析,发现27个化学成分为穴位贴敷组方治疗OIC的有效成分,22个靶点为穴位贴敷组方治疗OIC的作用靶点。其中芦荟大黄素、木犀草素、柚皮素及川陈皮素4关键个化学成分及AKT1、MAPK3、TNF、VEGFA、C
5、REB1、IL1B、MAPK8、MAPK1、HMOX19个关键靶点在穴位贴敷组方治疗OIC中发挥了重要的作用。分子对接结果显示关键化学成分与关键靶点具有较好的结合性;经PPI网络分析,发现AKT1与TNF、TNF与NOS2两组蛋白对关系密切互相作用在治疗OIC中发挥重要作用;经GO功能富集分析筛选得到生物学过程(BP)相关条目共117条,与OIC的治疗直接相关的通路有MAPK活性的激活、MAPK级联、ERK1和ERK2级联的正向调节、一氧化氮合酶活性的调控、一氧化氮生物合成过程的调控等。经KEGG通路富集分析筛选得到相关条目共93条,主要涉及肿瘤坏死因子信号通路、肿瘤信号通路、Toll样受体信
6、号通路、NOD样受体信号通路、MAPK信号通路等。结论:(1)个体化穴位贴敷及乳果糖治疗OIC均有疗效,且总体疗效个体化穴位贴敷优于乳果糖;个体化穴位贴敷在缩短首次排便时间及改善排便频率、排便不尽感及腹部疼痛方面优于乳果糖;且个体化穴位贴敷治疗OIC复发率低,远期疗效确切。(2)本研究通过网络药理学方法预测了穴位贴敷组方治疗OIC的有效化学成分及作用靶点,系统的阐释了其潜在的分子作用机制,为穴位贴敷治疗OIC提供了可靠的理论依据。关键词 阿片类药物相关性便秘 穴位贴敷 网络药理学 分子对接 作用机制AbstractObjective: (1) To study and observe the
7、clinical efficacy of individual acupoint application in the treatment of opioid-induced constipation. (2) To explore the mechanism of acupoint application prescription in the treatment of opioid-induced constipation by means of network pharmacology and molecular docking.Methods:(1) Clinical part: 70
8、 patients with opioid-related constipation were randomly divided into treatment group (n = 35) and control group (n = 35). The treatment group was treated with individual acupoint application and the control group was treated with lactulose. One week after treatment, the first defecation time, const
9、ipation symptom score (CCS score), stool character score (BSFS score) and adverse reactions were observed in the two groups before and after treatment, and the patients were followed up for one week after drug withdrawal to understand the recurrence of constipation. (2) The part of network pharmacol
10、ogy: TCMSP database, TCMID database and Chinese natural products chemical composition database were used to find the chemical components of acupoint application prescription, and the relevant literatures were consulted to supplement; the potential targets of chemical components were predicted throug
11、h TCMSP database and STITCH database, and the target egg white names were transformed into target gene names through UniProt database. At the same time, the targets related to OIC were screened by Genecards database, OMIM database and TTD database. The intersection targets were obtained by mapping t
12、he corresponding target of drug composition with disease target, and the relationship network of drug-chemical composition-intersection target-disease was constructed by using Cytoscape3.8.2 software, and the intersection targets were inputted into STRIING database to construct the PPI network relat
13、ed to OIC. Cytoscape3.8.2 software was used to visualize the PPI network, and the topology of the network was analyzed, the key targets of acupoint application prescription for the treatment of OIC were selected, while the corresponding chemical components of the key targets were reversed looking fo
14、r as the key chemical components. Schrodinger software was used for molecular docking to verify the reliability of the combination of key chemical components and key targets; The intersection targets were input into DAVID database for GO functional enrichment analysis and KEGG biological pathway enr
15、ichment analysis to further explore the mechanism of acupoint application prescription in the treatment of OIC.Results:(1) In the course of treatment, 5 patients fell off and were finally included in 65 cases, including 33 cases in the treatment group and 32 cases in the control group. There were si
16、gnificant differences in BSFS score, CCS score and individual symptom score between the two groups before treatment (P0.001), but there was no significant difference in the degree of defecation effort, defecation time, defecation assist type and the number of unsuccessful defecation per day between
17、the two groups after treatment (P0.001). The first defecation time, stool characteristics, defecation frequency, incomplete defecation and abdominal pain in the treatment group were better than those in the control group (P0.05). The total effective rate of the treatment group was 87.88% better than
18、 that of the control group (71.88%, P0.05). In the course of treatment, 1 patient in the treatment group had mild skin allergy and 2 patients in the control group had mild nausea, and the symptoms were relieved after symptomatic treatment. In terms of recurrence between the two groups, the recurrenc
19、e rate of 20.69% in the treatment group was significantly lower than that in the control group (47.83%, P0.05), and the recurrence time of drug withdrawal in the treatment group was later than that in the control group (P0.05). (2) Network pharmacology: through the biological network analysis of acu
20、point application prescription acting on the target of OIC, it was found that 27 chemical components were the effective components of acupoint application prescription in the treatment of OIC, and 22 targets were the target of acupoint application prescription in the treatment of OIC. Four key chemi
21、cal components of aloe emodin, luteolin, naringenin and nobilein and the key targets of AKT1, MAPK3, TNF, VEGFA, CREB1, IL1B, MAPK8, MAPK1 and HMOX1 play an important role in the treatment of OIC. The results of molecular docking verification showed that there was a good binding between the key chem
22、ical components and key targets, and by PPI network analysis, it was found that the close interaction between AKT1 and TNF, TNF and NOS2 played an important role in the treatment of OIC. A total of 117 (BP)-related items were screened by GO functional enrichment analysis. The pathways directly relat
23、ed to the treatment of OIC include the activation of MAPK activity, the cascade of MAPK, the positive regulation of ERK1 and ERK2 cascade, the regulation of nitric oxide synthase activity, the regulation of nitric oxide biosynthesis and so on. A total of 93 related items were screened by KEGG pathwa
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